A platform trial is a type of prospective, disease-focused, adaptive, randomized clinical trial (RCT) that compares multiple, simultaneous and possibly differently-timed interventions against a single, constant control group. As a disease-focused trial design (compared to an intervention-focused), platform trials attempt to answer the question "which therapy will best treat this disease". Platform trials are unique in their utilization of both: a common control group and their opportunity to alter the therapies it investigates during its active enrollment phase. Platform trials commonly take advantage of Bayesian statistics, but may incorporate elements of frequentist statistics and/or machine learning.
Purpose Platform trials can be a particularly useful design when researchers predict that multiple therapies that would become available at different times require investigation. For example, when the COVID-19 pandemic began, researchers predicted that there would eventually be multiple different therapies that could be investigated, but that these therapies would be discovered at different times in the pandemic timeline, therefore making a platform trial a useful design. Similar to COVID-19, platform trials have found use in oncology, alzheimer's disease and pneumonia research. Platform trials can be a superior design compared to simple 2-arm clinical trials when multiple therapies need investigation, because it only requires a single control group. This means that platform trials can be conducted with fewer enrolled patients than a set of potentially redundant control groups in a series of separate 2-arm trials. This in turn allows for results to be published sooner for time-sensitive diseases, and for fewer patients to be exposed to the risks of a clinical trial. Platform trials may be appropriate for phase II-IV trails.
Design elements
Master protocol Platform trials, like any clinical trial, have many elements that must be established before starting enrollment. While platform trials have the ability to alter their therapies of interest there are still many elements of these trials that remain constant and regulated. Such common, stable elements of platform trials described in the master protocol include: qualified trial staff members, trial sites, recruitment criteria, enrollment procedures, pre-set criteria for adding/discontinuing new therapies, adverse event reporting, communication plans, and statistical analysis plans. The master protocol is submitted to the IRB and once approved, only arm-specific appendices need to be submitted for Institutional Review Board (IRB) approval in the event of changes to the trial arms. Establishing a stable master protocol with adaptive therapy arms allows for faster, more efficient trial execution. Platform trials are often large, multi-site investigations and as a result, master protocols frequently try to identify common human and physical infrastructure to maximize resource availability and efficiency. Examples of this include identifying/creating a single IRB to review the trial for all sites, creating a single database for collecting data, and creating a single randomization mechanism for all enrolled patients.
Common control group One of the defining aspects of a platform trial is the shared control group that all interventional arms are compared to. Whereas a conventional RCT would generally have half of all enrolled patients in the control group; platform trials have a higher total number of patients in various interventional groups. This allows for fewer patients to be enrolled which saves money and accelerates completion time. A common statistical tool for determining allocation ratios, Dunnett's test, suggests that n t {\displaystyle n{\sqrt {t}}} patients should be allocated to the control group, where n {\displaystyle n} is the sample size for each of the active arms and t {\displaystyle t} is their number. As the number of arms increase, the ratio of patients allocated to control also increases. This results in the control group having a higher proportion of allocated patients than any one arm though platform trials still allow for more total patients to be in intervention arms than multiple 2-arm RCTs. While the control group is not necessarily designed to change in the way that the treatment arms are, because platform trials can run for long periods of time, control groups may have to evolve to stay current with standard of care. When this is the case, or if there is a change to patient demographics with time, later analysis of the trial must be careful to consider comparing investigational patients to only the appropriate subset of control patients.
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